TensorFlow 1.x Deep Learning Cookbook

How to do it...

We proceed with the recipe as follows:

1. Import the pre-built models and additional modules needed for processing and showing images:

from keras.applications.vgg16 import VGG16from keras.models import Modelfrom keras.preprocessing import imagefrom keras.applications.vgg16 import preprocess_inputimport numpy as np

2. Select a specific layer from the network and get the features produced as output:

# pre-built and pre-trained deep learning VGG16 modelbase_model = VGG16(weights='imagenet', include_top=True)for i, layer in enumerate(base_model.layers):print (i, layer.name, layer.output_shape)# extract features from block4_pool blockmodel =Model(input=base_model.input, output=base_model.get_layer('block4_pool').output)

3. Extract ...